Abstract

3D face recognition is attracting more attention
due to the recent development in 3D facial data acquisition
techniques. It is strongly believed that 3D Face recognition
systems could overcome the inherent problems of 2D face
recognition such as facial pose variation, illumination, and
variant facial expression. In this paper we present a novel
technique for 3D face recognition system using a set of
parameters representing the central region of the face. These
parameters are essentially vertical and cross sectional profiles
and are extracted automatically without any prior knowledge
or assumption about the image pose or orientation. In addition,
these profiles are stored in terms of their Fourier Coefficients
in order to minimize the size of input data. Our approach
is validated and verified against two different datasets of 3D
images covers enough systematic and pose variation. High
recognition rate was achieved.